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OBJECTIVE Prostate cancer (PCa) is one of the most commonly diagnosed cancers among men which is associated with profound metabolic changes. Systematic analysis of the metabolic alterations and identification of new biomarkers may benefit PCa diagnosis and a deep understanding of the pathological mechanism. The purpose of this study was to determine the metabolic features of PCa. METHODS Plasma and urine metabolites from 89 prostate cancer (PCa) patients, 84 benign prostatic hyperplasia (BPH) patients, and 70 healthy males were analyzed using LC-MS/MS and GC-MS. The Orthogonalised Partial Least Squares Discriminant Analysis (OPLS-DA) was used to find the significantly changed metabolites. The clinical value of the candidate markers was examined by receiver operating characteristic curve analysis and compared with prostate-specific antigen (PSA). RESULTS Multivariate statistical analyses found a series of altered metabolites, which related to the urea cycle, tricarboxylic acid cycle (TCA), fatty acid metabolism, and the glycine cleavage system. Plasma Glu/Gln showed the highest predictive value (AUC = 0.984) when differentiating PCa patients from healthy controls, with a higher sensitivity than PSA (96.6% vs. 94.4%). Both Glu/Gln and PSA displayed a low specificity when differentiating PCa patients from BPH patients (

The goal of this retrospective study was to evaluate the effect of surgical timing on patient outcomes after spontaneous intracerebral hemorrhage (ICH). We also identified risk factors associated with poor prognosis.We reviewed all patients who underwent surgery for ICH between January 2014 and January 2021. The outcome was measured using the modified Rankin Scale (mRS) score at 6 months after the surgery. Patients with mRS 0-2 were considered having favorable outcomes, and those with mRS 3-5 were considered having unfavorable outcomes. The relationships of surgical timing with the risk of unfavorable outcomes were identified using the interaction and stratified analyses, and generalized additive and logistic regression models. A nomogram was established and evaluated using a receiver operating characteristic curve analysis, plotted decision curve, and calibration curve.We identified 53 patients with favorable outcomes and 144 with unfavorable outcomes. The number of cases who underwent surgery at12 hours and36 hours in the favorable outcome group was more than that in the unfavorable outcome group (P0.001). When the time to operating room (TOR) was less than 21 hours, a shorter TOR was associated with unfavorable outcomes, using the smoothing spline analysis (odds ratio = 0.8, P0.001). Finally, we developed a nomogram using systolic blood pressure, Glasgow Coma Scale, midline shift, hematoma volume, and TOR for predicting the unfavorable outcome. The area under the curve, accuracy, specificity, and sensitivity of nomogram were 0.90, 0.87, 0.72, and 0.93, respectively.Surgical timing between 12 and 26 hours after ICH was associated with favorable outcomes. The nomogram including systolic blood pressure, Glasgow Coma Scale, midline shift, hematoma volume, and TOR was reliable for predicting the ICH outcome.

In recent years, convolutional neural networks (CNNs) have been widely used. However, their ever-increasing amount of parameters makes it challenging to train them with the GPUs, which is time and energy expensive. This has prompted researchers to turn their attention to training on more energy-efficient hardware. batch normalization (BN) layer has been widely used in various state-of-the-art CNNs for it is an indispensable layer in the acceleration of CNN training. As the amount of computation of the convolutional layer declines, its importance continues to increase. However, the traditional CNN training accelerators do not pay attention to the efficient hardware implementation of the BN layer. In this letter, we design an efficient CNN training architecture by using the systolic array. The processing element of the systolic array can support the BN functions both in the training process and the inference process. The BN function implemented is an improved, hardware-friendly BN algorithm, range batch normalization (RBN). The experimental results show that the implementation of RBN saves 10% hardware resources, reduces the power by 10.1%, and the delay by 4.6% on average. We implement the accelerator on the field programmable gate array VU440, and the power consumption of the its core computing engine is 8.9 W.

Great software engineers are essential to the creation of great software. However, today, we lack an understanding of what distinguishes great engineers from ordinary ones. We address this knowledge gap by conducting one of the largest mixed-method studies of experienced engineers to date. We surveyed 1,926 expert engineers, including senior engineers, architects, and technical fellows, asking them to judge the importance of a comprehensive set of 54 attributes of great engineers. We then conducted 77 email interviews to interpret our findings and to understand the influence of contextual factors on the ratings. After synthesizing the findings, we believe that the top five distinguishing characteristics of great engineers are writing good code, adjusting behaviors to account for future value and costs, practicing informed decision-making, avoiding making others’ jobs harder, and learning continuously. We relate the findings to prior work, and discuss implications for researchers, practitioners, and educators.

The spatial accessibility of prehospital EMS is particularly important for the elderly population’s physiological functions. Due to the recent expansion of aging populations all over the globe, elderly people’s spatial accessibility to prehospital EMS presents a serious challenge. An efficient strategy to address this issue involves using geographic information systems (GIS)-based tools to evaluate the spatial accessibility in conjunction with the spatial distribution of aging people, available road networks, and prehospital EMS facilities. This study employed gravity model and empirical Bayesian Kriging (EBK) interpolation analysis to evaluate the elderly’s spatial access to prehospital EMS in Ningbo, China. In our study, we aimed to solve the following specific research questions: In the study area, “what are the characteristics of the prehospital EMS demand of the elderly?” “Do the elderly have equal and convenient spatial access to prehospital EMS?” and “How can we satisfy the prehospital EMS demand of an aging population, improve their spatial access to prehospital EMS, and then ensure their quality of life?” The results showed that 37.44% of patients admitted to prehospital EMS in 2020 were 65 years and older. The rate of utilization of ambulance services by the elderly was 27.39 per 1000 elderly residents. Ambulance use by the elderly was the highest in the winter months and the lowest in the spring months (25.90% vs. 22.38%). As for the disease spectrum, the main disease was found to be trauma and intoxication (23.70%). The mean accessibility score was only 1.43 and nearly 70% of demand points had scored lower than 1. The elderly’s spatial accessibility to prehospital EMS had a central-outward gradient decreasing trend from the central region to the southeast and southwest of the study area. Our proposed methodology and its spatial equilibrium results could be taken as a benchmark of prehospital care capacity and help inform authorities’ efforts to develop efficient, aging-focused spatial accessibility plans.

Background: Previous study revealed that Genome-instability was correlated with tumor-immune microenvironment in cancer. We try to discriminate the prognosis, immunotherapy and poly (ADP)-ribose polymerase (PARP) inhibitor responses through comprehensive analysis of genome-instability related lncRNAs and the tumor-immune microenvironment in patients with low-grade glioma (LGG). Methods and Results: RNAseq data, genome variation profiling data and copy number variation (CNV) data were used to evaluate the genomic instability of LGG patients. Genomic unstable-like (GU-like) and genomic stable-like (GS-like) clusters were identified by hierarchical clustering analysis of 102 genome-instability related lncRNAs (GILncRNAs). GS-like cluster had a tendency to receive better clinical outcome. Patients in GU-like cluster were more likely to respond to immunotherapy, especially anti-PD-1/PD-L1 treatment. PARP inhibitors including Rucaparib and Olaparib will get better therapeutic effects for patients in GU-like cluster. Lasso and Cox regression analysis were utilized to construct the risk model based on GILncRNAs. As for the risk model constructed by 9 GILncRNAs, the overall survival, clinical outcome, immunotherapeutic response, and PARP inhibitor sensitivity were significantly different between patients of high and low-risk groups. Conclusions: The genome-instability related lncRNAs signature involved in our risk model had great advantages in predicting prognosis, immunotherapy and PARP inhibitor response.

Objective: A reliable prediction of clinical outcome is important for clinicians to set appropriate medical strategies in treating patients with aneurysmal subarachnoid hemorrhage (aSAH). In this study, we aim to establish a perioperative nomogram involving serum lipid signatures for predicting poor outcomes at 3 months in patients with aSAH following endovascular therapy.Methods: Data of patients with aSAH receiving endovascular therapy were collected. Univariable and multivariable analyses were performed to screen independent predictors related to unfavorable outcomes defined by the modified Rankin Scale (mFS) ≥3. A novel nomogram based on these significant features was conducted. The clinical application of this nomogram was assessed by decision curve analysis (DCA) and clinical impact curve.Results: A total number of patients included in this study were 213 (average age 58.9 years, 65.7% female), representing a poor 3-month outcome rate of 48.8%. Free fatty acid (FFA) levels on admission were efficient in predicting poor outcomes compared with other contents in serum lipids. Univariable and multivariable analyses revealed advanced age (P = 0.034), poor Hunt Hess (HH) (odds ratio, OR = 3.7, P < 0.001) and mFS (OR = 6.0, P < 0.001), aneurysms in the posterior circulation (OR = 4.4, P = 0.019), and higher FFA levels on admission (OR = 3.1, P = 0.021) were negative independent predictors of poor 3 months outcome. A novel nomogram composed of these significant features presented a concordance index (C-index) of 0.831 while the practical benefit was validated by DCA and clinical impact curve. An online calculator based on R programming promoted the clinical application of this nomogram.Conclusion: Nomogram involving age, HH grade, mFS, aneurysm location, and serum FFA levels was sufficient to provide an individualized prediction of 3-month poor outcome for each patient with aSAH who underwent endovascular therapy.

Engineering software to be inclusive of all those that might/could/should use the software is important. However, today, data used to engineer software can have inherent biases (e.g. gender identity) with inclusiveness concerns. While much attention has been given to this topic in the AI/ML space, in this paper, we examine another data-centric software engineering process, A/B testing, for which we have a dearth of understanding today. Using real-world data from the Windows out of box experience (OOBE) feature, we provide a case-study of how inclusiveness concerns can manifest in A/B testing, practical adjustments to A/B testing towards inclusive software engineering, and insights into ongoing challenges. We discuss implications for research and practice.

Castration‑resistant prostate cancer (CRPC) is a major challenge in the treatment of prostate cancer (PCa). Phospholipase Cε (PLCε), an oncogene, has been found to be involved in the carcinogenesis, tumor proliferation and migration of several types of cancer. The effects, however, of PLCε on CRPC remains unclear. In the present study, the expression of PLCε and glioma‑associated homolog (Gli)‑1/Gli‑2 in benign prostatic hyperplasia (BPH), PCa and CRPC tissues and cells was investigated, and the correlations between PLCε and Gli‑1/Gli‑2 in CRPC tissues and cell lines were further explored. In addition, the effect of PLCε on cell proliferation and invasion was assessed in CRPC cell lines, and the sensitivity of EN‑R and 22RV1 cells to enzalutamide following the downregulation of PLCε expression was determined using lentivirus‑mediated shPLCε and/or treatment with specific Gli inhibitor GANT61. It was found that the PLCε expression was excessively upregulated in the majority of CRPC tissues, and PLCε positivity was linked to poor progression‑free survival (PFS) and overall survival (OS) in patients with PCa. Furthermore, PLCε knockdown significantly suppressed CRPC cell proliferation and invasion. Of note, it was found that PLCε knockdown increased the sensitivity of CRPC cells to enzalutamide in vitro by suppressing androgen receptor (AR) activities via the non‑canonical Hedgehog/Gli‑2 and p‑STAT3 signaling pathways. PLCε knockdown was shown to increase the sensitivity of CRPC cell xenografts to enzalutamide in vivo. Finally, the combination of PLCε knockdown with GANT61 significantly sensitized CRPC cells to enzalutamide. Collectively, the results of the present study suggest that PLCε is a potential therapeutic target for CRPC.

Most prostate cancers (Pcas) develop into castration-resistant prostate cancer (CRPC) after receiving androgen deprivation therapy (ADT). The expression levels of PLCε and wnt3a are increased in Pca and regulate androgen receptor (AR) activity. However, the biological function and mechanisms of PLCε and wnt3a in CRPC remain unknown. In this study, we found that the expression levels of PLCε, wnt3a, and AR were significantly increased in CRPC tissues as well as bicalutamide-resistant-LNCaP and enzalutamide-resistant-LNCaP cells. In addition, PLCε knockdown partly restored the sensitivity of drug-resistant cells to bicalutamide and enzalutamide by inhibiting the activity of the wnt3a/β-catenin/AR signaling axis. Interestingly, the resistance of LNCaP cells docetaxel is related to PLCε but not the wnt3a/β-catenin pathway. We also found that the combination of PLCε knockdown and enzalutamide treatment synergistically suppressed cell proliferation, tumor growth, and bone metastasis using in vitro and in vivo experiments. Our study revealed that PLCε is involved in the progression of drug-resistance in CRPC and could be a new target for the treatment of CRPC.

Renewable energy resources especially wind and solar energy are emerging as the modern power sources to electrify remote areas. The main reason behind their emergence is due to their environment-friendly behavior, unlimited availability and short period for replenishment over nonrenewable energy resources. Renewable energy resources are much better than nonrenewable energy resources, but the intermittency in renewable energy resources degrades the system performance. In order to overcome the intermittency, multiple hybrid system techniques were proposed in literature that can achieve suitable results but have disadvantages of complicated control structures and high implementation cost. Considering aforementioned shortcomings, a simple balancing approach is proposed to intermix solar and wind energy together so as to utilize the available energy from both sources at a given time. It is very common that solar farms are the dominating source of energy in daytime and summer, while wind farms are the dominating source of energy at night and in winter. The proposed approach delivers maximum possible power to the load by combining dominating and non-dominating resources all the time, hence mitigating the intermittency of individual resources. Compared with other approaches, the proposed approach offers key benefits with redundancy, simple design and low cost, which can be analyzed from simulation results.

In order to effectively alleviate wind power consumption and environmental pollution, taking the grid restrictions and wind power consumption into consideration, a combined dispatching model of thermal-wind power system is proposed, which is helpful to arrange the output of generating units economically and reasonably. The wind power cogeneration scheduling model is built on the basis of minimizing the total operation cost which includes unit operation cost, environmental cost and wind abandonment cost. Besides, the grid restrictions are considered reasonably, inclueding DC power flow equation for fast calculation, constraints of generator operating range, limit constraint of unit slope, start/stop time limit, spinning reserve limitations and wind energy output constraints. The model is a quadratic programming model, which is solved by CPLEX in this paper. Taking IEEE30 electrical system as an illustration, the validity and rationality of the proposed method are verified.

Purpose To develop generative adversarial networks (GANs) that synthesize realistic anterior segment optical coherence tomography (AS-OCT) images and evaluate deep learning (DL) models that are trained on real and synthetic datasets for detecting angle closure. Methods The GAN architecture was adopted and trained on the dataset with AS-OCT images collected from the Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, synthesizing open- and closed-angle AS-OCT images. A visual Turing test with two glaucoma specialists was performed to assess the image quality of real and synthetic images. DL models, trained on either real or synthetic datasets, were developed. Using the clinicians' grading of the AS-OCT images as the reference standard, we compared the diagnostic performance of open-angle vs. closed-angle detection of DL models and the AS-OCT parameter, defined as a trabecular-iris space area 750 µm anterior to the scleral spur (TISA750), in a small independent validation dataset. Results The GAN training included 28,643 AS-OCT anterior chamber angle (ACA) images. The real and synthetic datasets for DL model training have an equal distribution of open- and closed-angle images (all with 10,000 images each). The independent validation dataset included 238 open-angle and 243 closed-angle AS-OCT ACA images. The image quality of real versus synthetic AS-OCT images was similar, as assessed by the two glaucoma specialists, except for the scleral spur visibility. For the independent validation dataset, both DL models achieved higher areas under the curve compared with TISA750. Two DL models had areas under the curve of 0.97 (95% confidence interval, 0.96-0.99) and 0.94 (95% confidence interval, 0.92-0.96). Conclusions The GAN synthetic AS-OCT images appeared to be of good quality, according to the glaucoma specialists. The DL models, trained on all-synthetic AS-OCT images, can achieve high diagnostic performance. Translational relevance The GANs can generate realistic AS-OCT images, which can also be used to train DL models.

After the pandemic of COVID-19, neutralizing antibodies (NAbs) against SARS-CoV-2 have been developed for the prophylactic and therapeutic purposes. However, few methodologies are described in detail on how to rapidly and efficiently generate effective NAbs to SARS-CoV-2. Here, we integrated and optimized a strategically screening method for NAbs, which has enabled us to obtain SARS-CoV-2 receptor-binding domain (RBD) specific NAbs within 6 days, followed by additional 9 days for antibody production and function analysis. Using this method, we obtained 198 specific Abs against SARS-CoV-2 RBD from the blood samples of COVID-19 convalescent patients, and 96 of them showed neutralizing activity. At least 20% of these NAbs exhibited advanced neutralizing potency and high affinity, with the top two NAbs showing half-maximal inhibitory concentration (IC50) to block authentic SARS-CoV-2 at 9.88 and 11.13 ng/ml, respectively. Altogether, our study provides an effective methodology with high applicable value for discovering potential preventative and therapeutic NAbs for the emerging infectious diseases.

BACKGROUND: Pulmonary arterial hypertension is a progressive angio-proliferative disease associated with high morbidity and mortality rates. Although the histopathology of pulmonary arterial hypertension is well described, its therapeutic option remains unsatisfactory. This study investigated the effect of celastrol treatment on right ventricular dysfunction, remodeling, and pulmonary vascular remodeling in pulmonary arterial hypertension rats as well as its possible mechanisms. METHODS: Pulmonary arterial hypertension was induced in male Sprague-Dawley rats by a single subcutaneously injection of monocrotaline. After daily delivery of celastrol (1 mg/kg) or vehicle via intraperitoneal injection for 4 weeks, the effects of celastrol on right ventricular function, fibrosis, and pulmonary vascular remodeling were assessed. The infiltration of macrophages, the expression of inflammatory cytokines, including MCP-1, IL-1β, IL-6, and IL-10, and the expression of NF-κB signaling pathway-associated proteins, IκBα, p-IKKα/β and p65 were further detected. Finally, the effect of celastrol on human pulmonary artery smooth cells proliferation under hypoxia was studied in vitro. RESULTS: Rats with pulmonary arterial hypertension had decreased right ventricular function, increased right ventricular fibrosis and pulmonary arteries with interstitial thickening and prominent media hypertrophy. Treatment with celastrol improved right ventricular function, attenuated right ventricular fibrosis and pulmonary vascular remodeling. Significantly decreased macrophage infiltration, reduced levels of pro-inflammatory cytokines, increased level of anti-inflammatory cytokine and inhibited NF-κB signaling pathway were observed in the lung tissues of rats treated with celastrol. Moreover, celastrol significantly suppressed the proliferation of human pulmonary artery smooth cells under hypoxia. CONCLUSIONS: We showed that in rats with pulmonary arterial hypertension, celastrol could improve right ventricular function, attenuate right ventricular and pulmonary vascular remodeling, and inhibit human pulmonary artery smooth cells proliferation under hypoxia. Suppression of the nuclear factor-κB (NF-κB) signaling pathway may be a part of the protective mechanism.

The treatment of castration-resistant prostate cancer (CRPC) remains challenging due to the failure of androgen deprivation therapy (ADT); hence the search for other molecular therapeutic targets besides androgen receptor signaling is ongoing. This study systematically investigated the expression of SOX17 and Notch receptors in CRPC tissues and cells in vitro, showing that consistent clinical CRPC, SOX17/Notch1, and Notch4 were responsible for enzalutamide resistance in CRPC cells. The γ secretase inhibitors, BMS-708163, GSI-IX, PF-3084014, and RO4929097 abrogated the enzalutamide resistance by inhibiting Notch1 or/and Notch4 in vitro, with GSI-IX and RO4929097 being more effective than BMS-708163 and PF-3084014 in reliving bone metastasis in vivo. In conclusion, the Notch1 and Notch4 inhibitors GSI-IX and RO4929097 are promising therapeutic agents for the treatment of CRPC.

Objectives Acute respiratory failure (ARF) is a common medical complication in patients with cervical traumatic spinal cord injury (TSCI). To identify independent predictors for ARF onset in patients who underwent cervical TSCI without premorbid respiratory diseases and to apply appropriate medical supports based on accurate prediction, a nomogram relating admission clinical information was developed for predicting ARF during acute care period. Methods We retrospectively reviewed clinical profiles of patients who suffered cervical TSCI and were emergently admitted to Qingdao Municipal Hospital from 2014 to 2020 as the training cohort. Univariate analysis was performed using admission clinical variables to estimate associated factors and a nomogram for predicting ARF occurrence was generated based on the independent predictors from multivariate logistic regression analysis. This nomogram was assessed by concordance index for discrimination and calibration curve with internal-validated bootstrap strategy. Receiver operating characteristic curve was conducted to compare the predictive accuracy between the nomogram and the traditional gold standard, which combines neuroimaging and neurological measurements by using area under the receiver operating characteristic curve (AUC). An additional 56-patient cohort from another medical center was retrospectively reviewed as the test cohort for external validation of the nomogram. Results 162 patients were eligible for this study and were included in the training cohort, among which 25 individuals developed ARF and were recorded to endure more complications. Despite the aggressive treatments and prolonged intensive care unit cares, 14 patients insulted with ARF died. Injury level, American Spinal Injury Association Impairment Scale (AIS) grade, admission hemoglobin (Hb), platelet to lymphocyte ratio, and neutrophil percentage to albumin ratio (NPAR) were independently associated with ARF onset. The concordance index of the nomogram incorporating these predictors was 0.933 in the training cohort and 0.955 in the test cohort, although both calibrations were good. The AUC of the nomogram was equal to concordance index, which presented better predictive accuracy compared with previous measurements using neuroimaging and AIS grade (AUC 0.933 versus 0.821, Delong’s test p p = 0.034). In addition, this nomogram was translated to a Web-based calculator that could generate individual probability for ARF in a visualized form. Conclusions The nomogram incorporating the injury level, AIS grade, admission Hb, platelet to lymphocyte ratio, and NPAR is a promising model to predict ARF in patients with cervical TSCI who are absent from previous respiratory dysfunction. This nomogram can be offered to clinicians to stratify patients, strengthen evidence-based decision-making, and apply appropriate individualized treatment in the field of acute clinical care.

As Machine Learning-based applications become increasingly pervasive, a growing concern is how to balance the need for large, representative data sets with the need to respect user data privacy. The increased compute and connectivity capabilities of edge devices (e.g. phones, PCs) presents us with new avenues for achieving this balance, including a promising approach known as federated learning with local privacy. However, today we have gaps in practical knowledge about applicability, trade-offs, and benefits for large-scale realworld implementation. In this paper, using large-scale data from a real-world Windows Update ML-driven application (as well as the publicly available CIFAR-10 data set to enhance reproducibility), we report empirical evaluations of four practical considerations: heterogeneity in device availability that may cause bias, resiliency of federated learning with local differential privacy, benefits of time-varying adaptive configurations, and data transmission/storage savings based on the Pareto principle. We discuss the implications of these findings for practitioners and researchers.

Because of its convenience and safety, percutaneous balloon compression (PBC) has become a more popular remedy for trigeminal neuralgia (TN) recently. The objective of this study was to establish a nomogram that can be used to preoperatively prognosticate the likelihood of pain-free based on preoperative disease characteristics. Clinical data were collected from those TN cases who had undergone PBC during the period of 2015 and 2020 in Qingdao Municipal Hospital. We excluded the cases caused by space-occupying lesion or had undergone MVD, percutaneous glycerol rhizotomy (PGR), and glycerol rhizotomy (GR). A nomogram was established based on the results of multivariable logistic analysis. A receiver operating characteristic curve (ROC) analysis was applied to evaluate the reliability of models. The plotted decision curves were also used to assess the net benefit of nomogram-assisted decisions. Internal validation was performed using the ROC by bootstrap sampling. Finally, 16 cases and 69 cases were included into the ineffective and effective groups respectively. In the crude, adjust I and adjust II models, response to carbamazepine positively, the grade II or III compression severity score, and classical TN type were all considered to be significant predictors of pain relief (BNI grades I-III) at 3 months' follow-up. The AUC, accuracy, specificity, and sensitivity of the nomogram system were 0.83, 0.85, 0.75, and 0.87 respectively for predicting patient outcomes. The decision curves showed good performance for the nomogram system in terms of clinical application, while more research with validation in multiple, external independent patient populations is needed.

This paper considers a closed-loop supply chain with single manufacturer, single retailer, and single third-party recycler, and the aim is to analyze the influence of government subsidy third-party recycler on the closed-loop supply chain strategies, and to consider the impact of different conversion coefficients of recovery cost on the closed-loop supply chain strategy from the perspective of third-party recovery effort cost. This paper uses KKT condition to solve the different decision models, then compares and analyzes the optimal strategy under the different decision models, and discusses the relationship between government subsidy and recovery cost conversion coefficient and pricing, expected recycling rate and system profit. Finally, some numerical experiments are conducted to verify the outcome. It is shown that government subsidies to third-party can effectively affect retail price, wholesale price, expected recycling rate, and supply chain system profit. That is, the higher the government subsidy is, the lower the retail price and wholesale price are, and the higher the expected recycling rate and the system profit are; but the recycling cost conversion coefficient has an opposite effect on retail price, wholesale price, expected recycling rate and system profits.

The coexistence of high penetration CHP(combined heat power) and large-scale wind power generation may cause severe wind power curtailment. However, in the north areas of China, particularly during winter, the application of the thermal energy storage(TES), the elasticity of CHP units operation and the heat load can help to reduce the curtailment. Hence, a new 3-level optimization model is built to realize the collaborative operation of CHP unit, TES equipment and heat load management. Then, On the basis of the two-phase transaction mode composed by traditional energy market and the peak shaving market, the optimal operation mode of CHP unit is proposed to provide peak shaving capacity for wind power curtailment, under a certain approved peak shaving price. At last, the typical influencing factors, including the capacity of TES equipment, different operation modes and peak load shaving price, are analyzed to show the economic benefits of the proposed method.

Neutralizing antibodies (Abs) have been considered as promising therapeutics for the prevention and treatment of pathogens. After the outbreak of COVID-19, potent neutralizing Abs to SARS-CoV-2 were promptly developed, and a few of those neutralizing Abs are being tested in clinical studies. However, there were few methodologies detailly reported on how to rapidly and efficiently generate neutralizing Abs of interest. Here, we present a strategically optimized method for precisive screening of neutralizing monoclonal antibodies (mAbs), which enabled us to identify SARS-CoV-2 receptor-binding domain (RBD) specific Abs within 4 days, followed by another 2 days for neutralization activity evaluation. By applying the screening system, we obtained 198 Abs against the RBD of SARS-CoV-2. Excitingly, we found that approximately 50% (96/198) of them were candidate neutralizing Abs in a preliminary screening of SARS-CoV-2 pseudovirus and 20 of these 96 neutralizing Abs were confirmed with high potency. Furthermore, 2 mAbs with the highest neutralizing potency were identified to block authentic SARS-CoV-2 with the half-maximal inhibitory concentration (IC50) at concentrations of 9.88 ng/ml and 11.13 ng/ml. In this report, we demonstrated that the optimized neutralizing Abs screening system is useful for the rapid and efficient discovery of potent neutralizing Abs against SARS-CoV-2. Our study provides a methodology for the generation of preventive and therapeutic antibody drugs for emerging infectious diseases.

Castration-resistant prostate cancer (CRPC) is a progressed stage of prostate cancer, which requires better understanding of the mechanisms and remains an unmet clinical need. As a common oncogene, K-Ras is associated with malignant behavior in different types of tumors but its role in CRPC is unknown. The present study aims to find the mechanism of K-Ras in CRPC and whether it can be used as a crucial molecule for the treatment of CRPC. For this purpose, tissue samples from primary prostate cancer (PPC) and CRPC patients were analyzed by immunohistochemistry and the data showed that K-Ras was elevated in CRPC. More importantly, higher K-Ras expression was related to a shorter recurrence-free survival time in patients with CRPC. In addition, K-Ras promoted the invasion, migration, and drug resistance of CRPC cells by activation of PLCε/PKCε signaling pathway. Meanwhile, the inhibitor of K-RasG12C mutants was able to inhibit malignant behavior of CRPC cells in vitro and in vivo. Inhibitors of K-RasG12C mutants have entered clinical trials. Taken together, the study shows that K-Ras may activate PKCε through PLCε, resulting in the alterations of malignant behavior of CRPC. Inhibitor 9, an inhibitor of the K-RasG12C mutant, has a strong anti-tumor effect in CRPC, which potentially suggests that inhibitors of this nature may serve as a promising treatment for CRPC.

Contamination of soil and water by waste from abandoned uranium mines has led to chronic exposures to metal mixtures in Native American communities. Our previous work demonstrated that community exposures to mine waste increase the likelihood of developing cardiovascular disease, as well as the likelihood of developing multiple chronic diseases including diabetes, hypertension and kidney disease. Exposure to various environmental metals is associated with elevated oxidative stress, which is considered a contributor to these and other chronic disease states. The purpose of the current research was to assess potential associations between exposure to uranium and arsenic and evidence for increased oxidative stress as measured by urinary F2 -isoprostanes in pregnant women enrolled in the Navajo Birth Cohort Study. The current study also included an analysis of zinc as a potential mediator of oxidative stress in the study population. Urinary arsenic and uranium, serum zinc and urinary F2 -isoprostanes were measured for each study participant at enrollment. Study participants were pregnant women with median age of 26.8; 18.9% were enrolled in the 1st trimester, 44.7% were enrolled in the 2nd trimester, and 36.4% were enrolled in the 3rd trimester. Median urinary metal levels were 5.5 and 0.016 µg/g creatinine for arsenic and uranium, respectively. Multivariable regression analysis indicated a significant association between arsenic exposure and the lipid peroxidation product 8-iso-prostaglandin F2α, controlling for zinc and trimester. No associations were detected with uranium despite evidence that levels were in the Navajo Birth Cohort samples were 2.3 times the median reported for women in the National Health and Nutrition Examination Survey (2011-12). Zinc was not found to have any causal mediation of the effects of the other metals on oxidative stress. The current work is consistent with other studies that have detected an association between arsenic and elevated oxidative stress. In contrast to arsenic, uranium did not appear to increase oxidative stress response in this study population. These findings are relevant to assessing the potential human impact of chronic exposure to mixed metal waste from abandoned uranium mines.

On the basis of fully grasping the characteristics of the era of Dazhi Moving Cloud, we discovered that the following problems existed in the education for credit information and propaganda in the era of Dazhi Moving Cloud: the lack of compound type credit information propaganda and education talent; the database of credit information culture has not yet been completed; intelligence, credit information, education, and education media are mainly traditional and have poor interaction; credit information and education lack of legal protection. Then it proposes strategies for the development of credit information education in Dazhi Mobile Cloud era: formulate a general plan for credit information education under the background of Dazhi Mobile Cloud, establish a multi-party cooperation mechanism based on Dazhi Cloud Shift Technology, and innovate a multi-disciplinary training model for credit information and education. The establishment of a large database of credit information culture laid a solid foundation for the propaganda and education of the credit information culture; accelerated the integration of old and new media; innovated the education model for credit information culture; and accelerated the credit information legislation.

With the application of big data in the field of education, information technology has made it easier to share educational resources. This article studies the current situation of the sharing of educational resources in higher education institutions. First of all, it elaborates on the concept and characteristics of education big data, conducts research on the status quo of college education resources sharing under the big data environment, analyzes the existing problems, and finally provides some suggestions on the sharing of college education resources in the context of big data for current status surveys.

The Paris Agreement, with its target of net-zero emissions by 2050, has forced the concrete industry to reduce its energy consumption and carbon emissions. Therefore, the development of green concrete with a lower environmental impact is urgently required. In this case study, alum sludge was used as both sand and cement replacement in concrete blocks, and the compressive behaviour of concrete blocks and constructed masonry walls was first investigated. For cement replacement, the strength of blocks decreased with increasing alum sludge ash (ASA) content when the cement replacement ratio was higher than 10% by weight. These results were attributed to the fact that the filler effect and pozzolanic reaction of ASA compensated for the cement dilution effect at a moderate replacement ratio. However, the cement dilution effect dominated the mechanism with further ASA addition. For sand replacement, 10% oven-dried alum sludge addition degraded the mechanical performance of blocks significantly due to high organic content, which might hinder cement hydration. The compression behaviour of masonry walls was also influenced by alum sludge, and the testing results showed that the sludge addition increased ductility of the masonry wall but decreased the strength insignificantly. Therefore, the sludge-derived blocks were suitable for masonry application. Furthermore, a life cycle assessment model was developed based on the designed sludge-derived cement supply chain in South Australia. The obtained results indicate that the annual reduced greenhouse gas emissions were around 1,3339,549 tons, which equaled to the amount of greenhouse gas released from 28,898 passenger vehicles driven for a year. Refereed/Peer-reviewed

Evidence on the relationship between the vitamin D pathway and outcomes in melanoma is growing, although it is not always clear. We investigated the impact of measured levels of sun exposure at diagnosis on associations of vitamin D receptor gene (VDR) polymorphisms and melanoma-death in 3336 incident primary melanoma cases. Interactions between six SNPs and a common 3′ end haplotype were significant (p

Background Semi-supervised learning algorithms can leverage an unlabeled dataset when labeling is limited or expensive to obtain. In the current study, we developed and evaluated a semi-supervised generative adversarial networks (GANs) model that detects closed-angle on anterior segment optical coherence tomography (AS-OCT) images using a small labeled dataset. Methods In this cross-sectional study, a semi-supervised GANs model was developed for automatic closed-angle detection training on a small labeled and large unsupervised training dataset collected from the Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong (JSIEC). The closed-angle was defined as iris-trabecular contact beyond the scleral spur in AS-OCT images. We further developed two supervised deep learning (DL) models training on the same supervised dataset and the whole dataset separately. The semi-supervised GANs model and supervised DL models' performance were compared on two independent testing datasets from JSIEC (515 images) and the Department of Ophthalmology (84 images), National University Health System, respectively. The diagnostic performance was assessed by evaluation matrices, including the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results For closed-angle detection using clinician grading of AS-OCT imaging as the reference standard, the semi-supervised GANs model showed comparable performance, with AUCs of 0.97 (95% CI, 0.96-0.99) and 0.98 (95% CI, 0.94-1.00), compared with the supervised DL model (using the whole dataset) [AUCs of 0.97 (95% CI, 0.96-0.99), and 0.97 (95% CI, 0.94-1.00)]. When training on the same small supervised dataset, the semi-supervised GANs achieved performance at least as well as, if not better than, the supervised DL model [AUCs of 0.90 (95% CI: 0.84-0.96), and 0.92 (95% CI, 0.86-0.97)]. Conclusions The semi-supervised GANs method achieves diagnostic performance at least as good as a supervised DL model when trained on small labeled datasets. Further development of semi-supervised learning methods could be useful within clinical and research settings. Trial registration number ChiCTR2000037892.

Organic-inorganic hybrid perovskite materials offer the potential for realization of low-cost and flexible next-generation solar cells fabricated by low-temperature solution processing. Although efficiencies of perovskite solar cells have dramatically improved up to 22.1% within the past 6 years, there is still considerable room for further improvement in device efficiency through development of smooth and large grain size perovskite films. Commonly, the smooth perovskite layers and large grains are alternative to CH3NH3PbI3-xClx. However, the previous one-step fabrication of CH3NH3PbI3-xClx using PbCl2 needs long annealing time. Herein, the active layer, a noncontinuous CH3NH3PbI3-xClx film with micrometre-level crystalline grain, was fabricated using a one-step spin-coating process followed by high-temperature annealing and exhibited an increased efficiency of 9.93%. This finding enables the formation of larger grain size perovskite films and the demonstration of efficient perovskite heterojunction solar cells.

Randomized controlled trials (i.e. A/B testing) is the gold standard for evaluating improvements and accelerating innovations in the digital space. Prior work has shown that qualitative user feedback is an effective and important tool in the analysis of A/B tests. However, manual inductive qualitative analysis of feedback-best practices today-is expensive and unscalable, which may lead to the omission of important insights about quality and user experiences. Prior work has shown various automated NLP algorithms to be effective in extracting insights from feedback in the digital domain. But we lack understanding of the differences in insights gained from a manual inductive qualitative analysis versus automated NLP algorithms, for analyzing digital randomized controlled trials (where a key objective is understanding differences between control and treatment conditions). In this paper, we compare insights from manual inductive qualitative analyses and from six automated NLP algorithms, using data from large-scale real-world digital randomized controlled trials. We find that collocation algorithms (notable, trigrams) are promising, providing similar insights as manual analyses with substantially lower cost; however, issues remain and improvements are needed. We discuss implications for future research and for operationalization.

As an effective approach of testing corona discharge, UV imaging technology is non-contact, sensitive and intuitive, thus with a bright application prospect in the fault detection of electric apparatus. Currently, the strength of corona discharge is usually represented by the photon number output by UV imager, but in field service, it is difficult to accurately determine and quantitatively control the measuring distance. As a result, the different detection results of photon number are less comparable. This paper first deduces the relationship between the image height of substation electric apparatus and the actual number of UV photons by establishing a model for actual UV photons calculating, and then obtains the statistical results of UV photons of insulators and grading rings in time of different measuring distances and image heights by conducting the field UV corona test. Finally, a new method of checking the actual photons of UV corona is proposed according to the proposed model and field test data. According to the research results, the checking of actual photon number after taking the image height of electric apparatus into account may effectively eliminate the impact of measuring distance during field UV detection.

Stable isotopes (δ(15)N, δ(18)O) can serve as tracers for sources of nitrogen in the receiving environment. Hong Kong discharges ~3×10(6)m(3)d(-1) of treated wastewater into the ocean from 68 facilities implementing preliminary to tertiary treatment. We sampled treated sewage from 18 plants across 5 treatment types and examined receiving seawater from northeast Hong Kong. We analyzed nitrate and nitrite (NO3(-)+NO2(-), hereafter NOx) ammonium (NH4(+)), phosphate (PO4(+)) concentrations and δ(15)NNOx, δ(18)ONOx. Sewage effluents contained high mean nutrient concentrations (NO3(-)=260μmolL(-1), NH4(+)=1400μmolL(-1), PO4(+)=50μmolL(-1)) with some indication of nitrogen removal in advanced treatment types. Mean δ(15)NNOx of sewage effluents from all plants and treatment types (12‰) was higher than natural sources and varied spatially and seasonally. There was no overall effect of sewage treatment type on δ(15)NNOx. A mass balance model indicated that sewage (>68%) remains a dominant source of nitrate pollution in seawater in Tolo Harbor.

Thin-films of Zinc Tin Oxide (ZTO) with an extremely high charge carrier mobility and superior optical transmittance are synthesized using a simple solution method. These ZTO films have been systematically studied for the application in inverted polymer solar cells (PSCs). The Hall effects measurements show that the charge mobility of the ZTO semiconductor is over 16.5 cm 2 .V −1 .S −1 , which is the highest mobility value ever reported for oxide buffer made by using solution process. By applying the ZTO buffer layer in the inverted PSCs of P3HT:PC 61 BM, the power conversion efficiency of the device is 30% higher than that of the devices made with other common buffer layers such as ZnO and TiO 2 . Light intensity-dependent JV studies and PL measurements also indicate that ZTO buffer layer reduces surface recombination. This work demonstrates that the solution-synthesized ZTO is a promising new buffer layer with superior electron extraction capability for the solar cells.

Objective To investigate how hepatocyte cell adhesion molecule (hepaCAM) regulates cancer energy metabolism through hypoxia-inducible factor (HIF-1α) in renal cell carcinoma (RCC). Materials and Methods The expression of hepaCAM and HIF-1α in RCC tissue samples was examined by immunohistochemistry. Glucose consumption and lactate production assays were used to detect metabolic activity in RCC cell lines. P65 and IκB kinase (IKKβ) mRNA and protein expression were detected using quantitative real-time polymerase chain reaction and western blotting, respectively. Nuclear translocation of P65 was observed by immunofluorescence staining after re-expressing hepaCAM. The luciferase reporter assay was applied to validate the transcriptional activity of HIF-1α. Results HIF-1α expression was elevated and hepaCAM suppressed in RCC compared with adjacent normal tissues. Furthermore, hepaCAM re-expression significantly decreased glycolytic metabolism in RCC cell lines, and reduced HIF-1α, IKKβ, and P65 expression. The expression of HIF-1α, GLUT1, LDHA, and PKM2 were further reduced with combined hepaCAM overexpression and treatment with the NF-κB inhibitor BAY11-7082, compared to hepaCAM overexpression alone. Additionally, hepaCAM decreased the transcriptional activity of HIF-1α and blocked P65 nuclear translocation by the NF-κB pathway. Conclusion Our data suggest that hepaCAM suppresses the Warburg effect via the HIF-1α/NF-κB pathway in RCC, which is a facilitating factor in hepaCAM-reduced tumorigenesis.

Software engineering teams are usually interdisciplinary, consisting of both software engineers and non-software-engineers. While numerous studies have examined the success and failure of software engineering efforts from the perspective of software engineers, little is known about perspectives of expert non-software-engineers. In this study, we interviewed 46 experts across 10 roles at Microsoft (artists, content developers, data scientists, design researchers, designers, electrical engineers, mechanical engineers, product planners, program managers, service engineers) about their collaborations---good and bad---with software engineers. Overall, our experts described great software engineers as masters of their own technical domain, open-minded to the input of others, proactively informing everyone, and seeing the big picture of how pieces fit together. We discuss implications of our findings for practitioners, educators, and researchers.

Functional verification has become a major challenge in the chip design area. To improve the efficiency of verification, it is necessary to choose appropriate verification method and tools. An important aspect of functional verification is RTL verification, simulation-based verification is main method in RTL verification. Based on FT-8 multi- core processor, we developed a configurable test stimulus acceleration method, loading the test stimulus into memory and L2 cache to speed up the processor instructions fetch, which can shorten simulation cycle and simulation time, reduce the verification cost and guaranteed the correctness of design.

The memristor was originally defined as one of the fundamental electrical elements which provided the vacant connection between charge and flux. So far, most of the research has concentrated on the unique features of the individual devices. And the overall behavior of the multiple memristive systems has not been fully studied. Especially, the lack of corresponding fault diagnosis method for complex memristor circuits makes all the existing applications based on the multiple memristor circuits unstable and shaky. In this paper, the composite properties of multiple memristor circuits are further investigated. Then a neotype parametric fault diagnosis approach for memristive networks is presented using the doublet generator, sensitivity method and fuzzy math method, which offers huge benefits in terms of accuracy and time consumption.

Aeromonas is regarded as an important pathogen of freshwater animals but little is known about the genetics of its antimicrobial resistance in Chinese aquaculture. The aim of this study was to investigate the presence of integrons and characterize multidrug resistant Aeromonas spp. isolated from diseased farmed freshwater animals. These animal samples included fish, ornamental fish, shrimp, turtles, and amphibians which were collected from 64 farms in Guangdong province of South China. One hundred and twelve Aeromonas spp. isolates were examined for antimicrobial resistance phenotypes and the presence of class 1 integron sequences. Twenty-two (19.6%) of these isolates carried a class 1 integron comprising six different gene insertion cassettes including drfA12-orfF-aadA2, drfA12-orfF, aac(6')-II-bla OXA-21 -cat3, catB3, arr-3, and dfrA17. Among these, drfA12-orfF-aadA2 was the dominant gene cassette array (63.6%, 14/22) and this is the first report of aac(6')-II-bla OXA-21 -cat3 in an Aeromonas hydrophila isolate from a Chinese giant salamander (Andrias davidianus). All the integron-positive strains were resistant to more than five agents and 22 contained other resistance genes including bla CTX-M-3, bla TEM-1, aac(6')-Ib-cr, and tetA. All integron-positive isolates also contained mutations in the quinolone resistance determining regions (QRDR). Our investigation demonstrates that freshwater animals can serve as a reservoir for pathogenic Aeromonas strains containing multiple drug-resistance integrons. This data suggests that surveillance for antimicrobial resistance of animal origin and a prudent and responsible use of antimicrobials in aquaculture is necessary in these farms.

The participation of natural resources in income distribution requires the backup of appropriate value theories and distribution systems. This paper will, from these two aspects, expound on the theoretical foundation for natural resources to participate in income distribution and the practical significance of this participation. It will also demonstrate that the theory of distribution by contribution of factors, which is based on the dualistic value theory, is a reasonable distribution system that balances intergenerational equity and ecological efficiency.

The authors propose a combined scatter reduction and correction method to improve image quality in cone beam computed tomography (CBCT). The scatter kernel superposition (SKS) method has been used occasionally in previous studies. However, this method differs in that a scatter detecting blocker (SDB) was used between the X-ray source and the tested object to model the self-adaptive scatter kernel. This study first evaluates the scatter kernel parameters using the SDB, and then isolates the scatter distribution based on the SKS. The quality of image can be improved by removing the scatter distribution. The results show that the method can effectively reduce the scatter artifacts, and increase the image quality. Our approach increases the image contrast and reduces the magnitude of cupping. The accuracy of the SKS technique can be significantly improved in our method by using a self-adaptive scatter kernel. This method is computationally efficient, easy to implement, and provides scatter correction using a single scan acquisition.

The solidification process, the formation mechanism and distribution law of microporosity of the ball milling machine head cover made by SVEDALA corporation of USA were simulated by computer. The Solidworks software was used to generate three-dimensional model of cast parts and the Hua-casting software was employed to simulate the casting process. The simulated results show that significant microporosity was found in the middle of two casting heads and at the place of gudgeon journal because of insufficient chilling degree. The processing rationality was judged through the computer-aided technology, by which some drawbacks of the traditional process were overcome and the process design quality was improved.

The paper points out that the deep reason why modern computer system fails to defense malware lies in that user has no right to control the access of information, and proposes an explicit authorization mechanism. Its basic idea is that user explicitly authorizes program the file set it can access, and monitor all file access operations; once program requests to access file out of the authorized file set, refuse it, and this means that the program is malicious or has design errors. Computers based on this novel mechanism can protect information from attacking reliably, and have good software and hardware compatibility. A testing system is presented to validate our theory.

The author gives an insight of some CNNs-based cryptosystems, and then figure out the encryption algorithm based on the Chebyshev neural network is not as secure as it is announced since any attacker is able to decrypt the cipher-text by network synchronization.